FSpH: Fitted spectral hashing for efficient similarity search

Spectral hashing (SpH) is an efficient and simple binary hashing method, which assumes that data are sampled from a multidimensional uniform distribution. However, this assumption is too restrictive in practice. In this paper we propose an improved method, fitted spectral hashing (FSpH), to relax th...

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Main Authors: ZHANG, Yong-Dong, WANG, Yu, TANG, Sheng, HOI, Steven C. H., LI, Jin-Tao
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/sis_research/3947
https://ink.library.smu.edu.sg/context/sis_research/article/4949/viewcontent/FSpH_2014.pdf
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spelling sg-smu-ink.sis_research-49492018-02-22T06:52:26Z FSpH: Fitted spectral hashing for efficient similarity search ZHANG, Yong-Dong WANG, Yu TANG, Sheng HOI, Steven C. H. LI, Jin-Tao Spectral hashing (SpH) is an efficient and simple binary hashing method, which assumes that data are sampled from a multidimensional uniform distribution. However, this assumption is too restrictive in practice. In this paper we propose an improved method, fitted spectral hashing (FSpH), to relax this distribution assumption. Our work is based on the fact that one-dimensional data of any distribution could be mapped to a uniform distribution without changing the local neighbor relations among data items. We have found that this mapping on each PCA direction has certain regular pattern, and could be fitted well by S-curve function (Sigmoid function). With more parameters Fourier function also fits data well. Thus with Sigmoid function and Fourier function, we propose two binary hashing methods: SFSpH and FFSpH. Experiments show that our methods are efficient and outperform state-of-the-art methods. 2014-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3947 info:doi/10.1016/j.cviu.2014.01.011 https://ink.library.smu.edu.sg/context/sis_research/article/4949/viewcontent/FSpH_2014.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Sigmoid function Fourier function Spectral hashing Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Sigmoid function
Fourier function
Spectral hashing
Databases and Information Systems
spellingShingle Sigmoid function
Fourier function
Spectral hashing
Databases and Information Systems
ZHANG, Yong-Dong
WANG, Yu
TANG, Sheng
HOI, Steven C. H.
LI, Jin-Tao
FSpH: Fitted spectral hashing for efficient similarity search
description Spectral hashing (SpH) is an efficient and simple binary hashing method, which assumes that data are sampled from a multidimensional uniform distribution. However, this assumption is too restrictive in practice. In this paper we propose an improved method, fitted spectral hashing (FSpH), to relax this distribution assumption. Our work is based on the fact that one-dimensional data of any distribution could be mapped to a uniform distribution without changing the local neighbor relations among data items. We have found that this mapping on each PCA direction has certain regular pattern, and could be fitted well by S-curve function (Sigmoid function). With more parameters Fourier function also fits data well. Thus with Sigmoid function and Fourier function, we propose two binary hashing methods: SFSpH and FFSpH. Experiments show that our methods are efficient and outperform state-of-the-art methods.
format text
author ZHANG, Yong-Dong
WANG, Yu
TANG, Sheng
HOI, Steven C. H.
LI, Jin-Tao
author_facet ZHANG, Yong-Dong
WANG, Yu
TANG, Sheng
HOI, Steven C. H.
LI, Jin-Tao
author_sort ZHANG, Yong-Dong
title FSpH: Fitted spectral hashing for efficient similarity search
title_short FSpH: Fitted spectral hashing for efficient similarity search
title_full FSpH: Fitted spectral hashing for efficient similarity search
title_fullStr FSpH: Fitted spectral hashing for efficient similarity search
title_full_unstemmed FSpH: Fitted spectral hashing for efficient similarity search
title_sort fsph: fitted spectral hashing for efficient similarity search
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/sis_research/3947
https://ink.library.smu.edu.sg/context/sis_research/article/4949/viewcontent/FSpH_2014.pdf
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